# Building a Lemmatizer and a Spell-checker for Sorani Kurdish

arXiv: https://arxiv.org/abs/1809.10763 · HTML: https://mlsanity.com/paper/1809.10763/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Sep 2018.

## Built on by (most cited first, 3 of 3)

- [Correcting Arabic Soft Spelling Mistakes using BiLSTM-based Machine Learning](https://mlsanity.com/paper/2108.01141/) (2021)
- [A Formal Description of Sorani Kurdish Morphology](https://mlsanity.com/paper/2109.03942/) (2021)
- [Hunspell for Sorani Kurdish Spell Checking and Morphological Analysis](https://mlsanity.com/paper/2109.06374/) (2021)

## Abstract (arXiv)

The present paper aims at presenting a lemmatization and a word-level error correction system for Sorani Kurdish. We propose a hybrid approach based on the morphological rules and a n-gram language model. We have called our lemmatization and error correction systems Peyv and Renus respectively, which are the first tools presented for Sorani Kurdish to the best of our knowledge. The Peyv lemmatizer has shown 86.7% accuracy. As for Renus, using a lexicon, we have obtained 96.4% accuracy while without a lexicon, the correction system has 87% accuracy. As two fundamental text processing tools, these tools can pave the way for further researches on more natural language processing applications for Sorani Kurdish.